Pub Date : 2024-02-01DOI: 10.1109/TMBMC.2024.3361443
Iman Mokari Bolhassan;Ali Abdali;Murat Kuscu
Molecular Communications (MC) is a bio-inspired paradigm for transmitting information using chemical signals, which can enable novel applications at the junction of biotechnology, nanotechnology, and information and communication technologies. However, designing efficient and reliable MC systems poses significant challenges due to the complex nature of the physical channel and the limitations of the micro/nanoscale transmitter and receiver devices. In this paper, we propose a practical microfluidic transmitter architecture for MC based on hydrodynamic gating, a widely utilized technique for generating chemical waveforms in microfluidic channels with high spatiotemporal resolution. We develop an approximate analytical model that can capture the fundamental characteristics of the generated molecular pulses, such as pulse width, pulse amplitude, and pulse delay, as functions of main system parameters, such as flow velocity and gating duration. We validate the accuracy of our model by comparing it with finite element simulations using COMSOL Multiphysics under various system settings. Our analytical model can enable the optimization of microfluidic transmitters for MC applications in terms of minimizing intersymbol interference and maximizing data transmission rate.
分子通信（MC）是一种利用化学信号传输信息的生物启发范式，可在生物技术、纳米技术以及信息和通信技术的交界处实现新的应用。然而，由于物理信道的复杂性以及微/纳米级发射器和接收器设备的局限性，设计高效可靠的 MC 系统面临着巨大挑战。在本文中，我们提出了一种基于流体动力门控的实用微流控发射器架构，这是一种广泛应用于在微流控通道中产生高时空分辨率化学波形的技术。我们建立了一个近似分析模型，该模型可以捕捉到所产生的分子脉冲的基本特征，如脉冲宽度、脉冲幅度和脉冲延迟，这些都是主要系统参数（如流速和选通持续时间）的函数。我们将模型与 COMSOL Multiphysics 在各种系统设置下进行的有限元模拟进行了比较，从而验证了模型的准确性。我们的分析模型可以帮助优化微流控应用中的微流控发射器，从而最大限度地减少符号间干扰和提高数据传输速率。
{"title":"Microfluidic Molecular Communication Transmitter Based on Hydrodynamic Gating","authors":"Iman Mokari Bolhassan;Ali Abdali;Murat Kuscu","doi":"10.1109/TMBMC.2024.3361443","DOIUrl":"https://doi.org/10.1109/TMBMC.2024.3361443","url":null,"abstract":"Molecular Communications (MC) is a bio-inspired paradigm for transmitting information using chemical signals, which can enable novel applications at the junction of biotechnology, nanotechnology, and information and communication technologies. However, designing efficient and reliable MC systems poses significant challenges due to the complex nature of the physical channel and the limitations of the micro/nanoscale transmitter and receiver devices. In this paper, we propose a practical microfluidic transmitter architecture for MC based on hydrodynamic gating, a widely utilized technique for generating chemical waveforms in microfluidic channels with high spatiotemporal resolution. We develop an approximate analytical model that can capture the fundamental characteristics of the generated molecular pulses, such as pulse width, pulse amplitude, and pulse delay, as functions of main system parameters, such as flow velocity and gating duration. We validate the accuracy of our model by comparing it with finite element simulations using COMSOL Multiphysics under various system settings. Our analytical model can enable the optimization of microfluidic transmitters for MC applications in terms of minimizing intersymbol interference and maximizing data transmission rate.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"10 1","pages":"185-196"},"PeriodicalIF":2.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-30DOI: 10.1109/TMBMC.2024.3360341
Zhen Cheng;Zhichao Zhang;Jie Sun
The data-driven detectors based on deep learning have promising applications in signal detection with unknown channel parameters of molecular communication via diffusion (MCvD) system. In this paper, a signal detector for cooperative multi-hop mobile MCvD system with amplify-forward relaying strategy by using Transformer-based model is proposed. The mathematical expressions of the numbers of received molecules when considering two transmission schemes including multi-molecule-type (MMT) and single-molecule-type (SMT) are derived in order to generate the training dataset. On this basis, the training dataset is used to train the Transformer-based model offline. Then the trained Transformer-based model is adopted to detect the received signal under unknown channel parameters under MMT and SMT. Numerical results show that the Transformer-based model performs the best detection ability in cooperative multi-hop mobile MCvD system with lowest bit error rate of signal detection compared with deep neural networks (DNN) detector and convolutional neural networks (CNN) detector.
{"title":"Signal Detection of Cooperative Multi-Hop Mobile Molecular Communication via Diffusion","authors":"Zhen Cheng;Zhichao Zhang;Jie Sun","doi":"10.1109/TMBMC.2024.3360341","DOIUrl":"https://doi.org/10.1109/TMBMC.2024.3360341","url":null,"abstract":"The data-driven detectors based on deep learning have promising applications in signal detection with unknown channel parameters of molecular communication via diffusion (MCvD) system. In this paper, a signal detector for cooperative multi-hop mobile MCvD system with amplify-forward relaying strategy by using Transformer-based model is proposed. The mathematical expressions of the numbers of received molecules when considering two transmission schemes including multi-molecule-type (MMT) and single-molecule-type (SMT) are derived in order to generate the training dataset. On this basis, the training dataset is used to train the Transformer-based model offline. Then the trained Transformer-based model is adopted to detect the received signal under unknown channel parameters under MMT and SMT. Numerical results show that the Transformer-based model performs the best detection ability in cooperative multi-hop mobile MCvD system with lowest bit error rate of signal detection compared with deep neural networks (DNN) detector and convolutional neural networks (CNN) detector.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"10 1","pages":"101-111"},"PeriodicalIF":2.2,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-02DOI: 10.1109/TMBMC.2023.3349326
Chengyi Zhang;Hao Yan;Qiang Liu;Kun Yang;Fuqiang Liu;Lin Lin
For a long time, people have carried out various studies on molecular communication (MC) and the Internet of Bio-Nanothings (IoBNT) in order to realize biomedical applications inside the human body. However, how to realize the communication between these applications and the outside body has become a new problem. In general, different components in the blood have different light absorption rates. Based on this, we propose a new through-body communication method. The nanomachine in the blood vessel transmits signals by releasing certain substances that can influence blood oxygen saturation. The change in blood oxygen saturation can be detected by an outside body device measuring the attenuation of the light through the blood. The framework of the entire communication system is proposed and mathematically modeled. Its error performance is discussed and evaluated. The mutual information (MI) of the designed communication system is also derived and calculated. This research will contribute to the realization of the connection of the IoBNT inside the human body to the outside device.
{"title":"Design and Analysis of a Through-Body Signal Transmission System Based on Human Oxygen Saturation Detection","authors":"Chengyi Zhang;Hao Yan;Qiang Liu;Kun Yang;Fuqiang Liu;Lin Lin","doi":"10.1109/TMBMC.2023.3349326","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3349326","url":null,"abstract":"For a long time, people have carried out various studies on molecular communication (MC) and the Internet of Bio-Nanothings (IoBNT) in order to realize biomedical applications inside the human body. However, how to realize the communication between these applications and the outside body has become a new problem. In general, different components in the blood have different light absorption rates. Based on this, we propose a new through-body communication method. The nanomachine in the blood vessel transmits signals by releasing certain substances that can influence blood oxygen saturation. The change in blood oxygen saturation can be detected by an outside body device measuring the attenuation of the light through the blood. The framework of the entire communication system is proposed and mathematically modeled. Its error performance is discussed and evaluated. The mutual information (MI) of the designed communication system is also derived and calculated. This research will contribute to the realization of the connection of the IoBNT inside the human body to the outside device.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"10 1","pages":"122-131"},"PeriodicalIF":2.2,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-22DOI: 10.1109/TMBMC.2023.3345590
{"title":"2023 Index IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Vol.9","authors":"","doi":"10.1109/TMBMC.2023.3345590","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3345590","url":null,"abstract":"","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"9 4","pages":"499-510"},"PeriodicalIF":2.2,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10372180","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139034111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-22DOI: 10.1109/TMBMC.2023.3342731
O. Tansel Baydas;Ozgur B. Akan
Molecular communication (MC) is a paradigm that employs molecules as information carriers, hence, requiring unconventional transceivers and detection techniques for the Internet of Bio-Nano Things (IoBNT). In this study, we provide a novel MC model that incorporates a spherical transmitter and receiver with partial absorption. This model offers a more realistic representation than receiver architectures in literature, e.g., passive or entirely absorbing configurations. An optimization-based technique utilizing particle swarm optimization (PSO) is employed to accurately estimate the cumulative number of molecules received. This technique yields nearly constant correction parameters and demonstrates a significant improvement of 5 times in terms of root mean square error (RMSE) compared to the literature. The estimated channel model provides an approximate analytical impulse response; hence, it is used for estimating channel parameters such as distance, diffusion coefficient, or a combination of both. The iterative maximum likelihood estimation (MLE) is applied for the parameter estimation, which gives consistent errors compared to the estimated Cramer-Rao Lower Bound (CLRB).
分子通信（MC）是一种利用分子作为信息载体的范例，因此，生物纳米物联网（IoBNT）需要非常规的收发器和检测技术。在本研究中，我们提供了一种新颖的 MC 模型，该模型包含具有部分吸收功能的球形发射器和接收器。与文献中的接收器架构（如无源或完全吸收配置）相比，该模型提供了更真实的表示。利用粒子群优化（PSO）的优化技术，可以准确估计接收到的分子累积数量。该技术可获得几乎不变的校正参数，与文献相比，在均方根误差 (RMSE) 方面显著提高了 5 倍。估算出的信道模型提供了近似的分析脉冲响应，因此可用于估算距离、扩散系数或两者的组合等信道参数。参数估计采用迭代最大似然估计 (MLE)，与估计的克拉默-拉奥下限 (CLRB) 相比，误差一致。
{"title":"Received Signal and Channel Parameter Estimation in Molecular Communications","authors":"O. Tansel Baydas;Ozgur B. Akan","doi":"10.1109/TMBMC.2023.3342731","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3342731","url":null,"abstract":"Molecular communication (MC) is a paradigm that employs molecules as information carriers, hence, requiring unconventional transceivers and detection techniques for the Internet of Bio-Nano Things (IoBNT). In this study, we provide a novel MC model that incorporates a spherical transmitter and receiver with partial absorption. This model offers a more realistic representation than receiver architectures in literature, e.g., passive or entirely absorbing configurations. An optimization-based technique utilizing particle swarm optimization (PSO) is employed to accurately estimate the cumulative number of molecules received. This technique yields nearly constant correction parameters and demonstrates a significant improvement of 5 times in terms of root mean square error (RMSE) compared to the literature. The estimated channel model provides an approximate analytical impulse response; hence, it is used for estimating channel parameters such as distance, diffusion coefficient, or a combination of both. The iterative maximum likelihood estimation (MLE) is applied for the parameter estimation, which gives consistent errors compared to the estimated Cramer-Rao Lower Bound (CLRB).","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"10 1","pages":"92-97"},"PeriodicalIF":2.2,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-21DOI: 10.1109/TMBMC.2023.3345145
Pranab Das;Dilwar Hussain Mazumder
Drug function study is vital in current drug discovery, design, and development. Determining the drug functions of a novel drug is time-consuming, complicated, expensive, and requires many experts and clinical testing phases. The computational-based drug function prediction activity has recently become more attractive due to its capability to reduce drug development design complexity, time, human resources, cost, chemical waste, and the risk of failure. The evolution of the computational model has advanced as an effective tool for predicting and analyzing drug functions, which are derived from Medical Subject Headings (MeSH). However, predicting drug functions still faces several difficulties. Therefore, an exhaustive literature survey was conducted that discusses the application of computational methods to predict drug functions in the past decade. Additionally, this paper discusses the utilization of drug functions as an input feature to predict adverse drug reactions and disease classification. This work also provides an overview of the computational models with their performance, multi-label problem transformation methods, drug properties, and their sources needed for the task of drug function prediction. Finally, unsolved issues, research gaps, and difficulties with the drug function prediction task have been summarized.
{"title":"Advances in Predicting Drug Functions: A Decade-Long Survey in Drug Discovery Research","authors":"Pranab Das;Dilwar Hussain Mazumder","doi":"10.1109/TMBMC.2023.3345145","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3345145","url":null,"abstract":"Drug function study is vital in current drug discovery, design, and development. Determining the drug functions of a novel drug is time-consuming, complicated, expensive, and requires many experts and clinical testing phases. The computational-based drug function prediction activity has recently become more attractive due to its capability to reduce drug development design complexity, time, human resources, cost, chemical waste, and the risk of failure. The evolution of the computational model has advanced as an effective tool for predicting and analyzing drug functions, which are derived from Medical Subject Headings (MeSH). However, predicting drug functions still faces several difficulties. Therefore, an exhaustive literature survey was conducted that discusses the application of computational methods to predict drug functions in the past decade. Additionally, this paper discusses the utilization of drug functions as an input feature to predict adverse drug reactions and disease classification. This work also provides an overview of the computational models with their performance, multi-label problem transformation methods, drug properties, and their sources needed for the task of drug function prediction. Finally, unsolved issues, research gaps, and difficulties with the drug function prediction task have been summarized.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"10 1","pages":"75-91"},"PeriodicalIF":2.2,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.1109/TMBMC.2023.3326009
{"title":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Publication Information","authors":"","doi":"10.1109/TMBMC.2023.3326009","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3326009","url":null,"abstract":"","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"9 4","pages":"C2-C2"},"PeriodicalIF":2.2,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10364886","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138739585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.1109/TMBMC.2023.3326011
{"title":"IEEE Communications Society Information","authors":"","doi":"10.1109/TMBMC.2023.3326011","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3326011","url":null,"abstract":"","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"9 4","pages":"C3-C3"},"PeriodicalIF":2.2,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10364920","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138739584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/TMBMC.2023.3338950
Hanlin Xiao;Kamela Dokaj;Ozgur B. Akan
Molecular communication, as implied by its name, uses molecules as information carriers for communication between objects. It has an advantage over traditional electromagnetic-wave-based communication in that molecule-based systems could be biocompatible, operable in challenging environments, and energetically undemanding. Consequently, they are envisioned to have a broad range of applications, such as in the Internet of Bio-Nano Things, targeted drug delivery, and agricultural monitoring. Despite the rapid development of the field, with an increasing number of theoretical models and experimental testbeds established by researchers, a fundamental aspect of the field has often been sidelined, namely, the nature of the molecule in molecular communication. The potential information molecules could exhibit a wide range of properties, making them require drastically different treatments when being modeled and experimented upon. Therefore, in this paper, we delve into the intricacies of commonly used information molecules, examining their fundamental physical characteristics, associated communication systems, and potential applications in a more realistic manner, focusing on the influence of their own properties. Through this comprehensive survey, we aim to offer a novel yet essential perspective on molecular communication, thereby bridging the current gap between theoretical research and real-world applications.
{"title":"What Really is “Molecule” in Molecular Communications? The Quest for Physics of Particle-Based Information Carriers","authors":"Hanlin Xiao;Kamela Dokaj;Ozgur B. Akan","doi":"10.1109/TMBMC.2023.3338950","DOIUrl":"10.1109/TMBMC.2023.3338950","url":null,"abstract":"Molecular communication, as implied by its name, uses molecules as information carriers for communication between objects. It has an advantage over traditional electromagnetic-wave-based communication in that molecule-based systems could be biocompatible, operable in challenging environments, and energetically undemanding. Consequently, they are envisioned to have a broad range of applications, such as in the Internet of Bio-Nano Things, targeted drug delivery, and agricultural monitoring. Despite the rapid development of the field, with an increasing number of theoretical models and experimental testbeds established by researchers, a fundamental aspect of the field has often been sidelined, namely, the nature of the molecule in molecular communication. The potential information molecules could exhibit a wide range of properties, making them require drastically different treatments when being modeled and experimented upon. Therefore, in this paper, we delve into the intricacies of commonly used information molecules, examining their fundamental physical characteristics, associated communication systems, and potential applications in a more realistic manner, focusing on the influence of their own properties. Through this comprehensive survey, we aim to offer a novel yet essential perspective on molecular communication, thereby bridging the current gap between theoretical research and real-world applications.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"10 1","pages":"43-74"},"PeriodicalIF":2.2,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139234475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-29DOI: 10.1109/TMBMC.2023.3336259
Guodong Yue;Guoying Lin;Qiang Liu;Kun Yang
Molecular communication (MC) is a significant technology in the field of nano-biology, which uses molecules as message carriers to transmit information. Diffusion channel model is the most common channel model base on Brownian motion in molecular communication since molecules can diffuse to the destination without the need of extra energy supply. However, the random Brownian motion brings high delay and uncertainty to the communication process and thus modulation methods are required to improve the communication performance. The molecular communication system in the SISO (Single Input Single Output) scenario will be seriously affected by ISI (Inter Symbol Interference). In MIMO (Multi-Input Multi-Output) scenario, since there are multiple transmitters and receivers, in addition to ISI, there will be ILI (Inter Link Interference) as well. At present, most modulations are based on the concentration, type, time and space of molecules and only focus on SISO scenario. In this study, inspired by the MoSK (Molecule Shift Keying) modulation method, we proposed a new joint modulation method for MIMO communication in order to minimize the effect of ISI and ILI. Numerical results show that compared with the current modulation scheme, the proposed scheme allows the MIMO system achieve better BER (Bit error rate) performance and transmission rate.
分子通讯（MC）是纳米生物学领域的一项重要技术，它利用分子作为信息载体来传输信息。扩散信道模型是分子通讯中最常见的基于布朗运动的信道模型，因为分子可以扩散到目的地而不需要额外的能量供应。然而，随机布朗运动会给通信过程带来高延迟和不确定性，因此需要采用调制方法来提高通信性能。在 SISO（单输入单输出）情况下，分子通信系统会受到 ISI（符号间干扰）的严重影响。在 MIMO（多输入多输出）情况下，由于有多个发射器和接收器，除了 ISI 外，还会出现 ILI（链路间干扰）。目前，大多数调制都是基于分子的浓度、类型、时间和空间，并且只关注 SISO 场景。本研究受 MoSK（分子移频键控）调制方法的启发，提出了一种用于 MIMO 通信的新型联合调制方法，以最大限度地降低 ISI 和 ILI 的影响。数值结果表明，与当前的调制方案相比，所提出的方案能使多输入多输出系统获得更好的误码率（BER）性能和传输速率。
{"title":"Diffusion-Based Anti-Interference Joint Modulation in MIMO Molecular Communication","authors":"Guodong Yue;Guoying Lin;Qiang Liu;Kun Yang","doi":"10.1109/TMBMC.2023.3336259","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3336259","url":null,"abstract":"Molecular communication (MC) is a significant technology in the field of nano-biology, which uses molecules as message carriers to transmit information. Diffusion channel model is the most common channel model base on Brownian motion in molecular communication since molecules can diffuse to the destination without the need of extra energy supply. However, the random Brownian motion brings high delay and uncertainty to the communication process and thus modulation methods are required to improve the communication performance. The molecular communication system in the SISO (Single Input Single Output) scenario will be seriously affected by ISI (Inter Symbol Interference). In MIMO (Multi-Input Multi-Output) scenario, since there are multiple transmitters and receivers, in addition to ISI, there will be ILI (Inter Link Interference) as well. At present, most modulations are based on the concentration, type, time and space of molecules and only focus on SISO scenario. In this study, inspired by the MoSK (Molecule Shift Keying) modulation method, we proposed a new joint modulation method for MIMO communication in order to minimize the effect of ISI and ILI. Numerical results show that compared with the current modulation scheme, the proposed scheme allows the MIMO system achieve better BER (Bit error rate) performance and transmission rate.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"10 1","pages":"112-121"},"PeriodicalIF":2.2,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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